Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective:To analyze the methylation characteristics of the lymphocyte-specific protein-tyrosine kinase (LCK) promoter region in the peripheral blood circulation of rheumatoid arthritis (RA) patients and its correlation with clinical indicators.Methods:Targeted methylation sequencing was used to compare the methylation levels of 7 CpG sites in the LCK promoter region in the peripheral blood of RA patients with healthy controls (HC) and osteoarthritis (OA) patients. Correlation analysis and ROC curve construction were performed with clinical information.Results:Non-parametric tests revealed that compared with HC [0.53(0.50, 0.57)] and OA patients [0.59(0.54, 0.62), H=47.17, P<0.001], RA patients [0.63(0.59, 0.68)] exhibited an overall increase in methylation levels. Simultaneously, when compared with the HC group [0.38(0.35, 0.41), 0.59(0.55, 0.63), 0.60(0.55, 0.64), 0.59(0.55, 0.63), 0.58(0.53, 0.62), 0.45(0.43, 0.49), 0.57(0.54, 0.61)], the RA group [0.46(0.42, 0.49), 0.70(0.65, 0.75), 0.70(0.66, 0.76), 0.70(0.65, 0.75), 0.69(0.64, 0.74), 0.55(0.51, 0.59), 0.68(0.63, 0.73)] showed a significant elevation in methylation levels at CpG sites cg05350315_60, cg05350315_80, cg05350315_95, cg05350315_101, cg05350315_104, cg05350315_128, and cg05350315_142, with statistically significant differences ( Z=-5.63, -5.89, -5.91, -5.89, -5.98, -5.95, -5.95, all P<0.001). Compared with the OA group [0.65(0.59, 0.69), 0.65(0.60, 0.69), 0.64(0.58, 0.68), 0.50(0.45, 0.54), 0.63(0.58, 0.67)], the RA group [0.70(0.66, 0.76), 0.70(0.65, 0.75), 0.69(0.64, 0.74), 0.55(0.51, 0.59), 0.68(0.63, 0.73)] exhibited a significant increase in methylation levels at CpG sites cg05350315_95, cg05350315_101, cg05350315_104, cg05350315_128, and cg05350315_142, with statistically significant differences ( Z=-3.56, -3.52, -3.60, -3.67, -3.62; P=0.036, 0.042, 0.031, 0.030, 0.030). Furthermore, Pearson correlation coefficient analysis revealed a positive correlation between the overall methylation level in this region and C-reactive protein (CRP) ( r=0.19, P=0.004) and erythrocyte sedimentation rate ( r=0.14, P=0.035). The overall methylation level of the LCK promoter region in the CRP (low) group [0.63 (0.58, 0.68)] was higher than that in the CRP (high) group [0.65(0.61, 0.70)], with statistically significant differences ( Z=2.60, P=0.009). Finally, by constru-cting a ROC curve, the discriminatory efficacy of peripheral blood LCK promoter region methylation levels for identifying RA patients, especially seronegative RA patients, from HC and OA groups was validated, with an AUC value of 0.78 (95% CI: 0.63, 0.93). Conclusion:This study provides insights into the methylation status and methylation haplotype patterns of the LCK promoter region in the peripheral blood of RA patients. The overall methylation level in this region is positively correlated with the level of inflammation and can be used to differentiate seronegative RA patients from the HC and OA patients.

It has been proposed by Basic Questions On Proper Therapies for Different Diseases Geographically （《素问·异法方宜论篇》） that "wei （痿） diseases should be treated by Daoyin （导引）". Furthermore， it is clarified that the indications of Daoyin are those conditions related to spleen and dampness caused by dampness pathogen， excessive food intake and less exercise， and mainly manifested as heavy limbs， fatigue and flaccidity， which is similar to the metabolic imbalance in the early stage of glucose or lipid metabolism disorder in modern medicine. Based on modern clinical and basic research evidence， Daoyin can inhibit the response of inflammation， alleviate oxidative stress， regulate intestinal microbiota， and modulate gene expression to improve metabolic abnormalities， and this will provide ideas for researches on the indications of Daoyin.

The purpose of this study was to enrich the genomic information and provide a basis for further development and utilization of Polygonatum kingianum. The fresh rhizome of P. kingianum was used as the experimental material, and the full-length transcriptome was sequenced by PacBio Sequel platform. The final measured polymerase reads were 1 120 485, with a total of 77.73 GB of data. In NR database, 41 864 homologous sequence alignments were aligned to 5 species; 40 506 were annotated in the KOG database and classified into 26 categories based on their functionality; 69 060 GO annotated 32 functional groups divided into 3 categories: cellular components, molecular functions, and biological processes; 45 779 annotations were added to 145 metabolic pathways in the KEGG database. Among them, there are 127 identified transcripts related to polysaccharide synthesis in the glycolysis/gluconeogenesis metabolic pathway, 144 in the starch and sucrose metabolic pathway, 85 in the amino acid sugar and nucleotide sugar metabolic pathway, and 69 in the fructose and mannose metabolic pathway. In addition, 1 781 transcription factors were detected, distributed in 37 transcription factor families; 180 293 SSR loci were detected, among which single base repeats accounted for the most, accounting for 30.48% of all base repeats, and at least five base repeats, accounting for only 0.14% of single base repeats. The results of this study provide important data supporting for enriching the genomic information of P. kingianum and exploring its effective biosynthetic pathway.

Nephrotic syndrome (NS) has a variety of classifications, pathogenesis and pathological types. Clinical diagnosis primarily relies on serum biochemistry, while the specific classification necessitates renal puncture for biopsy, which is hindered by poor patient compliance. Therefore, it is of great significance for clinical diagnosis to find a non-invasive and rapid method to reflect the classification and progression of nephrotic syndrome. In this study, LC-MS metabolomics combined with receiver operating characteristic (ROC) and multiple linear regression analysis was used to screen and identify potential biomarkers capable of reflecting the typing and progression of nephrotic syndrome. According to the statistical parameters VIP>1, P<0.05 and AUC>0.5 obtained from the orthogonal partial least squares discriminant analysis (OPLS-DA) model, five potential classification markers were screened to distinguish membranous nephropathy (MN) from IgA nephropathy (IgAN), including indoleacetic acid, isoleucine proline, DL-indole-3-lactic acid, D-phenylalanine and L-tryptophan. Furthermore, using estimated glomerular filtration rate (eGFR) as the dependent variable, a multiple linear regression analysis was conducted to identify the potential progression markers capable of reflecting the progression of MN to uremia. These metabolites included alanylleucine, 9-capryloylcarnitine, gluconic acid, caprylyl glycine and sebacic acid. Potential markers of progression of IgA nephropathy to uremia comprised alanylleucine, 9-capryloylcarnitine, caprylyl glycine, and sebacic acid. This study provides a theoretical basis for the discovery of potential classification and progression biomarkers of kidney disease, and also offers a methodological reference for future research in this area. The protocol was approved by the Ethics Committee of Shanxi Provincial People's Hospital [(2020) Provincial Medical Ke Lun Shen Zi No. 30].

Objective To study the relationship between waist-to-height ratio(WHtR)and new-onset cerebral infarction in the elderly with hypertension.Methods A total of 9 096 elderly hypertensive patients were enrolled from the Kailuan study population.Using the first occurrence of cerebral infarction as the endpoint event,a prospective cohort study was performed.According to the WHtR value of the subjects with an interval of 0.05,the subjects were divided into G1 group(WHtR＜0.45),G2 group(0.45≤WHtR＜0.50),G3 group(0.50≤WHtR＜0.55),and G4 group(WHtR≥0.55).The cumulative incidence rate of endpoint event in each population were statistically analyzed using the life table method.Cox proportional hazards regression analysis was used to explore the role of WHtR in the occurrence of new cerebral infarction.Model 1 was a single factor Cox proportional hazards analysis model,only considering the influence of WHtR on the risk of cerebral infarction.After adjusting sex,age,body weight,serum hypersensitive C-reactive protein,systolic blood pressure,serum triglycerides,smoking history,fasting blood glucose,alcohol consumption,high-density lipoprotein cholesterol,diastolic blood pressure,exercise,low-density lipoprotein cholesterol,educational level,antihypertensive drug history,model 2 was established to observe the influence of WHtR on the occurrence of new-onset cerebral infarction.Results The follow-up lasted(9.3±2.7)years.Compared to the G2 group,multivariate Cox proportional hazards regression model showed that the hazard ratio HR(95%CI)for cerebral infarction in model 1 was 1.00(0.67～1.50),1.29(1.05～1.60)and 1.36(1.12～1.66)respectively in G1,G3 and G4;and that in model 2 was 1.09(0.72～1.65),1.24(0.99～1.54)and 1.31(1.05～1.62)respectively in G1,G3 and G4.Conclusion The risk of cerebral infarction in the elderly with hypertension is the lowest when WHtR between 0.45≤WHtR＜0.50,and WHtR greater than or equal to 0.55 is associated with an increased risk of new-onset cerebral infarction.

Objective To evaluate the efficacy and safety of Chinese patent medicine combined with inhalation therapy for bronchial asthma in children with network meta-analysis.Methods CNKI,CBM,Wanfang Data,VIP,Embase,PubMed,and Web of Science were searched for obtaining the clinical randomized controlled trials of Chinese patent medicine combined with inhalation therapy for the treatment of bronchial asthma in children.Stata14 was used for network meta-analysis of the data.Results A total of 28 studies were eventually included,involving seven kinds of Chinese patent medicines,namely Hanchuan Zupa Granules,Huaiqihuang Granules,Tanreqing Injection,Xiaoer Feire Kechuan Granules,Chuankezhi Injection,Yupingfeng Granules and Zhubei Dingchuan Pills.The results of network meta-analysis showed that for improving the total effective rate,Tanreqing Injection combined with inhalation therapy,Chuankezhi Injection combined with inhalation therapy,and Zhubei Dingchuan Pills combined with inhalation therapy had the top 3 rankings of surface under the cumulative ranking curve(SUCRA).The optimal intervention measures to improve the peak expiratory flow(PEF),forced expiratory volume at one second(FEV1),and the ratio of FEV1 to forced vital capacity(FEV1/FVC)may separately be Tanreqing Injection combined with inhalation therapy,Hanchuan Zupa Granules combined with inhalation therapy,and Zhubei Dingchuan Pills combined with inhalation therapy.The analysis of the SUCRA ranking of the incidence of adverse reactions showed that Xiaoer Feire Kechuan Granules combined with inhalation therapy may be the intervention with the least side effects,and Zhubei Dingchuan Pills combined with inhalation therapy may be the intervention with greater side effects.Conclusion Compared with inhalation therapy alone,Chinese patent medicine combined with inhalation therapy can enhance the effective rate of bronchial asthma in children and improve lung function indicators,and has good safety.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective:To investigate the influence of curative-intent resection with textbook outcomes of liver surgery (TOLS) on long-term prognosis of gallbladder carcinoma (GBC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 824 patients with GBC in the national multicenter database of Biliary Surgery Group of Elite Group of Chinese Journal of Digestive Surgery, who were admitted to 15 medical centers from January 2014 to January 2021, were collected. There were 285 males and 539 females, aged (62±11)years. According to the evalua-tion criteria of TOLS, patients were divided into those who achieved TOLS and those who did not achieve TOLS. Measurement data with normal distribution were represented as Mean± SD, and com-parison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Comparison of ordinal data were conduc-ted using the Mann-Whitney U test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX stepwise regression model with backward Wald method was used for univariate and multivariate analyses. Results:(1) Achievement of TOLS. Of the 824 patients undergoing curative-intent resection for GBC, there were 510 cases achieving TOLS and 314 cases not achieving TOLS. (2) Follow-up. Of the 824 patients undergoing curative-intent resection for GBC, after excluding 112 deaths within 90 days after discharge, 712 cases were included for the survival analysis. The median follow-up time, median overall survival time and 5-year overall survival rate of the 510 patients achieving TOLS were 22.1(11.4,30.1)months, 47.6(30.6,64.6)months and 47.5%. The median follow-up time, median overall survival time and 5-year overall survival rate of the 202 patients not achieving TOLS were 14.0(6.8,25.5)months, 24.3(20.0,28.6)months and 21.0%. There was a significant difference in overall survival between patients achieving TOLS and patients not achieving TOLS ( χ2=58.491, P<0.05). (3) Analysis of factors influencing prognosis of patients. Results of multivariate analysis showed that TOLS, carcinoembryonic antigen (CEA), CA19-9, poorly differentiation of tumor, T2 stage of eighth edition of American Joint Committee on Cancer (AJCC) staging, T3 and T4 stage of eighth edition of AJCC staging, N1 stage of the eighth edition of AJCC staging, N2 stage of the eighth edition of AJCC staging, adjuvant therapy were independent factors influencing overall survival time of patients undergoing curative-intent resection for GBC ( hazard ratio=0.452, 1.479, 1.373, 1.612, 1.455, 1.481, 1.835, 1.978, 0.538, 95% c onfidence interval as 0.352-0.581, 1.141-1.964, 1.052-1.791, 1.259-2.063, 1.102-1.920, 1.022-2.147, 1.380-2.441, 1.342-2.915, 0.382-0.758, P<0.05). Conclusion:Patients under-going curative-intent resection for GBC with TOLS can achieve better long-term prognosis.